This repository contains user-authored notes and summaries of the DeepLearning.ai Coursera specialization, which covers five courses on deep learning fundamentals. Topics include neural network architecture, hyperparameter tuning, regularization, optimization algorithms, convolutional networks, and sequence models. The notes cover concepts like CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, and initialization strategies, with examples implemented in Python and TensorFlow.